Optimizing Bearing Fault Diagnosis in Rotating Electrical Machines Using Deep Learning and Frequency Domain Features by Eduardo Quiles-Cucarella, Alejandro García-Bádenas, Ignacio Agustí-Mercader, Guillermo Escrivá-Escrivá

“…The analysis evaluates the effectiveness of two wavelet transforms (amor and morse) for feature extraction in correlation with varying learning rates. …”
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Early Detection of Lung Cancer Using Predictive Modeling Incorporating CTGAN Features and Tree-Based Learning by Abdulrahman Alzahrani

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SAVL: Scene-Adaptive UAV Visual Localization Using Sparse Feature Extraction and Incremental Descriptor Mapping by Ganchao Liu, Zhengxi Li, Qiang Gao, Yuan Yuan

“…Firstly, to tackle the challenge of inaccurate localization resulting from sparse terrain features, this work proposes a novel feature extraction network grounded in a general visual model, leveraging the robust zero-shot generalization capability of the pre-trained model and extracting sparse features from UAV and satellite imagery. …”
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DSAT: a dynamic sparse attention transformer for steel surface defect detection with hierarchical feature fusion by Shouluan Wu, Hui Yang, Liefa Liao, Chao Song, Yating Fang, Jianglong Fu, Tan Li

“…These defects exhibit diverse morphological characteristics and complex patterns, which pose substantial challenges to traditional detection models, particularly regarding multi-scale feature extraction and information retention across network depths. …”
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Machine learning-based feature selection for ultra-high-dimensional survival data: a computational approach by Nahid Salma, Majid Khan Majahar Ali, Raja Aqib Shamim

“…This study evaluates machine learning (ML)-based feature selection methods to address limitations in scalability, feature redundancy, and predictive accuracy in UHD RCC survival data. …”
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Kidney Ensemble-Net: Enhancing Renal Carcinoma Detection Through Probabilistic Feature Selection and Ensemble Learning by Zaib Akram, Kashif Munir, Muhammad Usama Tanveer, Atiq Ur Rehman, Amine Bermak

“…Our approach begins by acquiring spatial features from contrast-enhanced images using a Convolutional Neural Network (CNN) effectively capturing intricate patterns and structures characteristic of different carcinoma subtypes. …”
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Comparative Analysis of Deep Learning-Based Feature Extraction and Traditional Classification Approaches for Tomato Disease Detection by Hakan Terzioğlu, Adem Gölcük, Adnan Mohammad Anwer Shakarji, Mateen Yilmaz Al-Bayati

“…Twenty-one deep learning models were evaluated, and the top five performers (EfficientNet-b0, NasNet-Large, ResNet-50, DenseNet-201, and Places365-GoogLeNet) were selected for feature extraction. …”
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Individualized spatial network predictions using Siamese convolutional neural networks: A resting-state fMRI study of over 11,000 unaffected individuals. by Reihaneh Hassanzadeh, Rogers F Silva, Anees Abrol, Mustafa Salman, Anna Bonkhoff, Yuhui Du, Zening Fu, Thomas DeRamus, Eswar Damaraju, Bradley Baker, Vince D Calhoun

“…The proposed framework evaluates whether pairs of spatial networks (e.g., visual network and auditory network) are capable of subject identification and assesses the spatial variability in different network pairs' predictive power in an extensive whole-brain analysis. …”
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Multimodal Morphometric Similarity Network Analysis of Autism Spectrum Disorder by Antonio Del Casale, Darvin Shehu, Maria Camilla Rossi-Espagnet, Clarissa Zocchi, Irene Bilotta, Jan Francesco Arena, Alessandro Alcibiade, Barbara Adriani, Daniela Longo, Carlo Gandolfo, Andrea Romano, Stefano Ferracuti, Alessandro Bozzao, Antonio Napolitano

“…Structural connectivity was assessed using cortical morphometric features. Global and regional network indices, including the density index, node degree, node strength, and clustering coefficients, were evaluated. …”
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Concrete Crack Detection and Segregation: A Feature Fusion, Crack Isolation, and Explainable AI-Based Approach by Reshma Ahmed Swarna, Muhammad Minoar Hossain, Mst. Rokeya Khatun, Mohammad Motiur Rahman, Arslan Munir

“…The proposed method fuses features from concrete surface images through a ResNet-50 convolutional neural network (CNN) and curvelet transform handcrafted (HC) method, optimized by linear discriminant analysis (LDA), and the eXtreme gradient boosting (XGB) classifier then uses these features to recognize cracks. …”
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Handwritten Words Image Character Extraction Adaptive Algorithm Based on the Multi-branch Structure by GUO Xiaojing, ZHAO Xiaoyuan, ZOU Songlin

“…Second, features extracted from different layers represent varying dimensions in the feature matrix. …”
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A Study on Evaluation of Modular Suppliers and Discussion of Stability by Wei He

“…Evaluation of modular suppliers is a crucial step towards building an effective modular production network. …”
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Research on FAHP based Trojan attack effect evaluation by Chen-xi ZENG, Quan-yuan WU, Ai-ping LI, Rong JIANG

“…The particular characters of Trojan are not fully taken into consideration by existed network attack effect evaluation systems which mainly focus on DDoS and Warm.A few Trojan harm measurement systems is somewhat short for objectivity and completeness as the result of that its indicator values is confined to manually marked and qualitative values.Under the circumstances,the analysis of Trojan's features were started from,and a hierarchical index system which accepted both quantitative and qualitative values,and both manually marked and system col-lected values was built.Then,a FAHP based evaluation model was proposed to evaluate the Trojan attack effect.Meanwhile,a many-to-one method to ensemble multiple weight vectors was proposed.Finally,the rationality of proposed evaluation system was verified by comparison with others.…”
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Perceptual objective evaluation for multimodal medical image fusion by Chuangeng Tian, Juyuan Zhang, Lu Tang

“…However, rare research has been dedicated to the MMIF objective evaluation. In this study, we present a multi-scale aware attention network for MMIF quality evaluation. …”
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An Improved RFID-Based Localization Algorithm for Wireless Sensor Networks by Ayong Ye, Yuanjing Ling, Li Xu, Xiaoliang Yang

“…The position of RFID-tagged objects in sensor networks is becoming an important feature for ubiquitous computing applications. …”
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Practical classification accuracy of sequential data using neural networks by Mamoru Mimura

“…Utilizing both standard and specific neural network models, we conducted experiments to adapt this metric to neural networks and various feature extraction techniques. …”
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An Approach Based on Sum Product Networks for Code Smells Detection by Mostefai Abdelkader

“…This paper introduces a method (CSDSPN) based on a sum product network (SPN); a probabilistic deep architecture not yet evaluated in the context of code smell detection. …”
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Contrastive Learning‑based Simplified Graph Convolutional Network Recommendation by YU Yuchen, WU Siqi, ZHAO Qinghua, WU Xuhong, WANG Lei

“…[Purposes] Considering the problems of the existing Graph Convolutional Network (GCN) recommendation models, such as low model convergence efficiency, over-smoothing, and deteriorative recommendations for long-tail items caused by the effect of high-degree nodes on presentation learning, a Contrastive Learning-based Simplified Graph Convolutional Network recommendation algorithm (SGCN-CL) is presented. …”
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Head-Related Transfer Function Selection Using Neural Networks by Shu-Nung YAO, Tim COLLINS, Chaoyun LIANG

“…The shapes and sizes of listeners’ heads and pinnas were measured using digital photography; the measured anthropometric parameters form the feature vectors used by the neural network. A graphical user interface (GUI) was developed for participants to listen to music transformed using different HRTFs and to evaluate the fitness of each HRTF dataset. …”
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An optimization-inspired intrusion detection model for software-defined networking by Hui Xu, Longtan Bai, Wei Huang

“…As an emerging network architecture, software-defined networking (SDN) has the core concept of separating the control plane from the network hardware and unifying its management by a central controller. …”
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